Ahmed Abdulla, Ahmed Salaheldin, Kempe Daniel, Rådegran Göran
Department of Clinical Sciences Lund, The Section for Cardiology, Lund University, Lund, Sweden.
The Haemodynamic Lab, The Section for Heart Failure and Valvular Disease, Heart and Lung Medicine, Skåne University Hospital, Lund, Sweden.
Eur Heart J Open. 2023 Feb 21;3(2):oead012. doi: 10.1093/ehjopen/oead012. eCollection 2023 Mar.
Estimation of prognosis in pulmonary arterial hypertension (PAH) has been influenced by that various risk stratification models use different numbers of prognostic parameters, as well as the lack of a comprehensive and time-saving risk assessment calculator. We therefore evaluated the various European Society of Cardiology (ESC)-/European Respiratory Society (ERS)-based three- and four-strata risk stratification models and established a comprehensive internet-based calculator to facilitate risk assessment.
Between 1 January 2000 and 26 July 2021, 773 clinical assessments on 169 incident PAH patients were evaluated at diagnosis and follow-ups. Risk scores were calculated using the original Swedish Pulmonary Arterial Hypertension Registry (SPAHR)/Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) three-strata model, the updated SPAHR three-strata model with divided intermediate risk, and the simplified three-parameter COMPERA 2.0 four-strata model. The original SPAHR/COMPERA and the updated SPAHR models were tested for both 3-6 and 7-11 available parameters, respectively. Prognostic accuracy [area under the receiver operating characteristic (ROC) curve (AUC)] and Uno's cumulative/time-dependent C-statistics (uAUC) were calculated for 1-, 3-, and 5-year mortality. At baseline, both the original SPAHR/COMPERA and the updated SPAHR models, using up to six parameters, provided the highest accuracy (uAUC = 0.73 for both models) in predicting 1-, 3-, and 5-year mortality. At follow-ups, the updated SPAHR model with divided intermediate risk (7-11 parameters) provided the highest accuracy for 1-, 3-, and 5-year mortality (uAUC = 0.90), followed by the original SPAHR/COMPERA model (7-11 parameters) (uAUC = 0.88) and the COMPERA 2.0 model (uAUC = 0.85).
The present study facilitates risk assessment in PAH by introducing a comprehensive internet-based risk score calculator (https://www.svefph.se/risk-stratification). At baseline, utilizing the original or the updated SPAHR models using up to six parameters was favourable, the latter model additionally offering sub-characterization of the intermediate risk group. Our findings support the 2022 ESC/ERS pulmonary hypertension guidelines' strategy for risk stratification suggesting the utilization of a three-strata model at baseline and a simplified four-strata model at follow-ups. Our findings furthermore support the utility of the updated SPAHR model with divided intermediate risk, when a more comprehensive assessment is needed at follow-ups, complementing the three-parameter COMPERA 2.0 model. Larger multi-centre studies are encouraged to validate the utility of the updated SPAHR model.
By introducing an internet-based risk score calculator (https://www.svefph.se/risk-stratification), risk assessment is facilitated. Our results support the 2022 ESC/ERS pulmonary hypertension guidelines' risk stratification strategy, additionally suggesting the updated SPAHR three-strata model with divided intermediate risk, as a promising complement to the new simplified three-parameter COMPERA 2.0 four-strata strategy, when a more comprehensive overview is needed.
肺动脉高压(PAH)的预后评估受到多种因素影响,不同的风险分层模型使用的预后参数数量不同,且缺乏一个全面且省时的风险评估计算器。因此,我们评估了各种基于欧洲心脏病学会(ESC)/欧洲呼吸学会(ERS)的三层和四层风险分层模型,并建立了一个基于互联网的综合计算器以促进风险评估。
在2000年1月1日至2021年7月26日期间,对169例PAH初发患者进行了773次临床评估,包括诊断时和随访时的评估。使用原始的瑞典肺动脉高压注册研究(SPAHR)/肺动脉高压新启动治疗比较、前瞻性注册研究(COMPERA)三层模型、具有细分中度风险的更新后的SPAHR三层模型以及简化的三参数COMPERA 2.0四层模型计算风险评分。分别对原始的SPAHR/COMPERA模型和更新后的SPAHR模型在有3 - 6个和7 - 11个可用参数的情况下进行测试。计算1年、3年和5年死亡率的预后准确性[受试者操作特征(ROC)曲线下面积(AUC)]以及Uno的累积/时间依赖性C统计量(uAUC)。在基线时,原始的SPAHR/COMPERA模型和更新后的SPAHR模型,使用多达六个参数,在预测1年、3年和5年死亡率方面提供了最高的准确性(两个模型的uAUC均为0.73)。在随访时,具有细分中度风险的更新后的SPAHR模型(7 - 11个参数)在预测1年、3年和5年死亡率方面提供了最高的准确性(uAUC = 0.90),其次是原始的SPAHR/COMPERA模型(7 - 11个参数)(uAUC = 0.88)和COMPERA 2.0模型(uAUC = 0.85)。
本研究通过引入一个基于互联网的综合风险评分计算器(https://www.svefph.se/risk - stratification)促进了PAH的风险评估。在基线时,使用多达六个参数的原始或更新后的SPAHR模型是有利的,后者模型还对中度风险组进行了亚分类。我们的研究结果支持2022年ESC/ERS肺动脉高压指南的风险分层策略,即建议在基线时使用三层模型,在随访时使用简化的四层模型。我们的研究结果还支持在随访时需要更全面评估时,具有细分中度风险的更新后的SPAHR模型的实用性,它补充了三参数COMPERA 2.0模型。鼓励开展更大规模的多中心研究来验证更新后的SPAHR模型的实用性。
通过引入基于互联网的风险评分计算器(https://www.svefph.se/risk - stratification),促进了风险评估。我们的结果支持2022年ESC/ERS肺动脉高压指南的风险分层策略,此外还表明具有细分中度风险的更新后的SPAHR三层模型,当需要更全面的概述时,是新的简化三参数COMPERA 2.0四层策略的一个有前景的补充。